PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83
software that serves to draw. This jobs are very expensive and takes a lot of time. This study aims to improve the quality of grayscale images so that the results obtained have a better quality than the initial image, implementing techniques to improve image quality by creating a colorless image (gr...
| Main Authors: | , |
|---|---|
| Format: | Thesis |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2012
|
| Subjects: |
| _version_ | 1826046013879615488 |
|---|---|
| author | , Muhammad Safrizal , Drs. Agus Harjoko,M.Sc, Ph.D |
| author_facet | , Muhammad Safrizal , Drs. Agus Harjoko,M.Sc, Ph.D |
| author_sort | , Muhammad Safrizal |
| collection | UGM |
| description | software that serves to draw. This jobs are very expensive and takes a lot of
time. This study aims to improve the quality of grayscale images so that the
results obtained have a better quality than the initial image, implementing
techniques to improve image quality by creating a colorless image (grayscale
image) into a color image, build a system that can be utilized to improve the
quality of grayscale images, and compare of k-means clustering method and
hierarchical agglomerative clustering methods for coloring grayscale images.
Expected to be the basis of scientific development and implementation of image
processing systems for improving the quality of grayscale image into a more
complex color images.
color The image is converted into the � ! color spaces. Luminance �! and
gray value of each image are grouped based on proximity of each element. Color
mapping is done by transferring the value of chrome !! to be added in the gray
value of each element grayscale image with similarity between each centroid color
images and.
The results obtained in this study is a grayscale image color depends on the
amount of a given cluster, the selection of the reference image categories and the
influence of each color image in the same category. Testing staining based on
subjective analysis and objective analysis that has been done can be concluded
that the application of k-means clustering method is better than the application of
agglomerative hierarchical clustering methods in coloring grayscale images. |
| first_indexed | 2024-03-13T22:46:37Z |
| format | Thesis |
| id | oai:generic.eprints.org:118445 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T22:46:37Z |
| publishDate | 2012 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1184452016-03-04T08:47:53Z https://repository.ugm.ac.id/118445/ PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 , Muhammad Safrizal , Drs. Agus Harjoko,M.Sc, Ph.D ETD software that serves to draw. This jobs are very expensive and takes a lot of time. This study aims to improve the quality of grayscale images so that the results obtained have a better quality than the initial image, implementing techniques to improve image quality by creating a colorless image (grayscale image) into a color image, build a system that can be utilized to improve the quality of grayscale images, and compare of k-means clustering method and hierarchical agglomerative clustering methods for coloring grayscale images. Expected to be the basis of scientific development and implementation of image processing systems for improving the quality of grayscale image into a more complex color images. color The image is converted into the � ! color spaces. Luminance �! and gray value of each image are grouped based on proximity of each element. Color mapping is done by transferring the value of chrome !! to be added in the gray value of each element grayscale image with similarity between each centroid color images and. The results obtained in this study is a grayscale image color depends on the amount of a given cluster, the selection of the reference image categories and the influence of each color image in the same category. Testing staining based on subjective analysis and objective analysis that has been done can be concluded that the application of k-means clustering method is better than the application of agglomerative hierarchical clustering methods in coloring grayscale images. [Yogyakarta] : Universitas Gadjah Mada 2012 Thesis NonPeerReviewed , Muhammad Safrizal and , Drs. Agus Harjoko,M.Sc, Ph.D (2012) PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=58398 |
| spellingShingle | ETD , Muhammad Safrizal , Drs. Agus Harjoko,M.Sc, Ph.D PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title | PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title_full | PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title_fullStr | PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title_full_unstemmed | PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title_short | PERBANDINGAN PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN METODE K-MEANS CLUSTERING DAN AGGLOMERATIVE HIERARCHICAL CLUSTERING83 |
| title_sort | perbandingan pewarnaan citra grayscale menggunakan metode k means clustering dan agglomerative hierarchical clustering83 |
| topic | ETD |
| work_keys_str_mv | AT muhammadsafrizal perbandinganpewarnaancitragrayscalemenggunakanmetodekmeansclusteringdanagglomerativehierarchicalclustering83 AT drsagusharjokomscphd perbandinganpewarnaancitragrayscalemenggunakanmetodekmeansclusteringdanagglomerativehierarchicalclustering83 |